Comparing tl-moments, l-moments and conventional moments of dagum distribution by simulated data
Modeling income, wage, wealth, expenditure and various other socialvariables have always been an issue of great concern. The Dagum distributionis considered quite handy to model such type of variables. Our focus inthis study is to derive the L-moments and TL-moments of this distributionin closed for...
- Autores:
-
Shahzad, Mirza Naveed
Asghar, Zahid
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/73208
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/73208
http://bdigital.unal.edu.co/37683/
- Palabra clave:
- Dagum distribution
L-moments
Method of moments
Parameter estimation
TL-moments
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Modeling income, wage, wealth, expenditure and various other socialvariables have always been an issue of great concern. The Dagum distributionis considered quite handy to model such type of variables. Our focus inthis study is to derive the L-moments and TL-moments of this distributionin closed form. Using L and amp; TL-moments estimators we estimate the scaleparameter which represents the inequality of the income distribution fromthe mean income. Comparing L-moments, TL-moments and conventionalmoments, we observe that the TL-moment estimator has lessbias and rootmean square errors than those of L and conventional estimators consideredin this study. We also find that the TL-moments have smaller root meansquare errors for the coefficients of variation, skewness and kurtosis. Theseresults hold for all sample sizes we have considered in our Monte Carlo simulationstudy. |
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